Abstract Neural Radiance Field (NeRF) significantly degrades when only a limited number
of views are available. To complement the lack of 3D information, depth-based models, such …

We present GauHuman a 3D human model with Gaussian Splatting for both fast training (1 2
minutes) and real-time rendering (up to 189 FPS) compared with existing NeRF-based …

In this study, we introduce a methodology for human image animation by leveraging a 3D
human parametric model within a latent diffusion framework to enhance shape alignment …

Real-time rendering of photorealistic and controllable human avatars stands as a
cornerstone in Computer Vision and Graphics. While recent advances in neural implicit …

We introduce GoMAvatar a novel approach for real-time memory-efficient high-quality
animatable human modeling. GoMAvatar takes as input a single monocular video to create …

Despite recent research advancements in reconstructing clothed humans from a single
image, accurately restoring the “unseen regions” with high-level details remains an …

Creating high-quality 3D models of clothed humans from single images for real-world
applications is crucial. Despite recent advancements accurately reconstructing humans in …

In recent years, Neural Radiance Fields (NeRF) has made remarkable progress in the field
of computer vision and graphics, providing strong technical support for solving key tasks …

Generating 3D models lies at the core of computer graphics and has been the focus of
decades of research. With the emergence of advanced neural representations and …

As it is hard to calibrate single-view RGB images in the wild, existing 3D human mesh
reconstruction (3DHMR) methods either use a constant large focal length or estimate one …